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Dissecting the binding mechanisms of transcription factors to DNA using a statistical thermodynamics framework
Transcription Factors (TFs) bind to DNA and control activity of target genes. Here, we present ChIPanalyser, a user-friendly, versatile and powerful R/Bioconductor package predicting and modelling the binding of TFs to DNA. ChIPanalyser performs similarly to state-of-the-art tools, but is an explain...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708957/ https://www.ncbi.nlm.nih.gov/pubmed/33304457 http://dx.doi.org/10.1016/j.csbj.2020.11.006 |
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author | Martin, Patrick C.N. Zabet, Nicolae Radu |
author_facet | Martin, Patrick C.N. Zabet, Nicolae Radu |
author_sort | Martin, Patrick C.N. |
collection | PubMed |
description | Transcription Factors (TFs) bind to DNA and control activity of target genes. Here, we present ChIPanalyser, a user-friendly, versatile and powerful R/Bioconductor package predicting and modelling the binding of TFs to DNA. ChIPanalyser performs similarly to state-of-the-art tools, but is an explainable model and provides biological insights into binding mechanisms of TFs. We focused on investigating the binding mechanisms of three TFs that are known architectural proteins CTCF, BEAF-32 and su(Hw) in three Drosophila cell lines (BG3, Kc167 and S2). While CTCF preferentially binds only to a subset of high affinity sites located mainly in open chromatin, BEAF-32 binds to most of its high affinity binding sites available in open chromatin. In contrast, su(Hw) binds to both open chromatin and also partially closed chromatin. Most importantly, differences in TF binding profiles between cell lines for these TFs are mainly driven by differences in DNA accessibility and not by differences in TF concentrations between cell lines. Finally, we investigated binding of Hox TFs in Drosophila and found that Ubx binds only in open chromatin, while Abd-B and Dfd are capable to bind in both open and partially closed chromatin. Overall, our results show that TFs display different binding mechanisms and that our model is able to recapitulate their specific binding behaviour. |
format | Online Article Text |
id | pubmed-7708957 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-77089572020-12-09 Dissecting the binding mechanisms of transcription factors to DNA using a statistical thermodynamics framework Martin, Patrick C.N. Zabet, Nicolae Radu Comput Struct Biotechnol J Research Article Transcription Factors (TFs) bind to DNA and control activity of target genes. Here, we present ChIPanalyser, a user-friendly, versatile and powerful R/Bioconductor package predicting and modelling the binding of TFs to DNA. ChIPanalyser performs similarly to state-of-the-art tools, but is an explainable model and provides biological insights into binding mechanisms of TFs. We focused on investigating the binding mechanisms of three TFs that are known architectural proteins CTCF, BEAF-32 and su(Hw) in three Drosophila cell lines (BG3, Kc167 and S2). While CTCF preferentially binds only to a subset of high affinity sites located mainly in open chromatin, BEAF-32 binds to most of its high affinity binding sites available in open chromatin. In contrast, su(Hw) binds to both open chromatin and also partially closed chromatin. Most importantly, differences in TF binding profiles between cell lines for these TFs are mainly driven by differences in DNA accessibility and not by differences in TF concentrations between cell lines. Finally, we investigated binding of Hox TFs in Drosophila and found that Ubx binds only in open chromatin, while Abd-B and Dfd are capable to bind in both open and partially closed chromatin. Overall, our results show that TFs display different binding mechanisms and that our model is able to recapitulate their specific binding behaviour. Research Network of Computational and Structural Biotechnology 2020-11-12 /pmc/articles/PMC7708957/ /pubmed/33304457 http://dx.doi.org/10.1016/j.csbj.2020.11.006 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Martin, Patrick C.N. Zabet, Nicolae Radu Dissecting the binding mechanisms of transcription factors to DNA using a statistical thermodynamics framework |
title | Dissecting the binding mechanisms of transcription factors to DNA using a statistical thermodynamics framework |
title_full | Dissecting the binding mechanisms of transcription factors to DNA using a statistical thermodynamics framework |
title_fullStr | Dissecting the binding mechanisms of transcription factors to DNA using a statistical thermodynamics framework |
title_full_unstemmed | Dissecting the binding mechanisms of transcription factors to DNA using a statistical thermodynamics framework |
title_short | Dissecting the binding mechanisms of transcription factors to DNA using a statistical thermodynamics framework |
title_sort | dissecting the binding mechanisms of transcription factors to dna using a statistical thermodynamics framework |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708957/ https://www.ncbi.nlm.nih.gov/pubmed/33304457 http://dx.doi.org/10.1016/j.csbj.2020.11.006 |
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